Plus Vibe AI + Bruin
Ingest Plus Vibe AI data into your warehouse with incremental loading, quality checks, and full lineage. Defined in YAML, version-controlled in Git.
For business teams
What you get
Analysis beyond built-in reports
Join Plus Vibe AI behavioral data with revenue, support, and CRM data. Answer questions Plus Vibe AI alone can't.
Trusted behavioral data
Quality checks catch tracking gaps, duplicate events, and missing timestamps before they corrupt your models.
Self-serve for analysts
Plus Vibe AI data lands in your warehouse where analysts already work. No more exporting, no more waiting.
Real user journeys
Combine Plus Vibe AI events with purchase and support data to see the full customer journey, not just the product funnel.
For data & engineering teams
How it works
Event schema validation
Check for null event IDs, missing timestamps, and duplicate events on every sync. Catch tracking issues at ingestion.
YAML-defined, Git-versioned
Your Plus Vibe AI pipeline is a YAML file. Review in PRs, deploy with CI/CD, roll back with git revert.
SQL + Python transforms
Transform raw Plus Vibe AI events into funnels, cohorts, and user journeys with SQL or Python — in the same pipeline.
Dependency-aware scheduling
Bruin resolves pipeline dependencies automatically. Transforms only run after Plus Vibe AI data has landed.
Before you start
Step 1
Add your Plus Vibe AI connection
Connect using Plus Vibe AI API key and workspace ID. Add this to your Bruin environment file — credentials are stored securely and referenced by name in your pipeline YAML.
Parameters
api_keyPlus Vibe AI API keyworkspace_idYour workspace ID
connections:
plusvibeai:
type: plusvibeai
uri: "plusvibeai://?api_key=<api_key>&workspace_id=<workspace_id>"Step 2
Create your pipeline
Define a YAML asset that tells Bruin what to pull from Plus Vibe AI and where to land it. This file lives in your Git repo — reviewable, version-controlled, and deployable with CI/CD.
Available tables
name: raw.plusvibeai_campaigns
type: ingestr
parameters:
source_connection: plusvibeai
source_table: 'campaigns'
destination: bigqueryStep 3
Add quality checks
Add column-level and custom SQL checks to your Plus Vibe AI data. If a check fails, the pipeline stops — bad data never reaches downstream models or dashboards.
columns:
- name: event_id
checks:
- name: not_null
- name: unique
- name: event_timestamp
checks:
- name: not_null
custom_checks:
- name: data is fresh
query: |
SELECT MAX(event_timestamp) >
TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 24 HOUR)
FROM raw.plusvibeai_campaignsStep 4
Run it
One command. Bruin connects to Plus Vibe AI, pulls data incrementally, runs your quality checks, and lands clean data in your warehouse. If a check fails, the pipeline stops — bad data never reaches downstream.
--start-date$ bruin run .Running pipeline...
plusvibeai_campaigns
✓ Fetched 2,847 new records
✓ Quality: campaign_id not_null PASSED
✓ Quality: spend not_null PASSED
✓ Quality: no negative ad spend PASSED
✓ Loaded into bigquery
Completed in 12sOther Analytics integrations
Ready to connect Plus Vibe AI?
Start for free, or book a demo to see how Bruin handles ingestion, quality, lineage, and scheduling for your entire data stack.